Research On WSNs Coverage Optimization Strategy For Moving Targets

Wireless Sensor Networks(WSNs)are composed of a large number of tiny,low-power sensor nodes.With its advantages of easy deployment and strong information processing ability,WSNs are often used in sensitive areas such as battlefields and borders to monitor illegal intruders.In the above application fields,there are two schemes to optimize the coverage of anti-intrusion monitoring for moving targets.One is how to cover the whole monitoring area as quickly as possible at the least cost,so that illegally intruded moving targets can be monitored in time from any place;The other is applied in some special fields.In view of the worst case of WSNs coverage,the network deployment cost is fully considered,and the weak coverage area is found by using the Minimum Exposure Path(MEP)and improved to prevent unauthorized objects from passing through the monitoring area.Traditional WSNs has many defects in the first scheme.First of all,in order to meet the coverage requirements,the sensor nodes are usually randomly scattered on a large scale for initial deployment,which not only makes the deployment cost huge,but also leads to uneven distribution of nodes,resulting in coverage redundancy and coverage holes,thus threatening the coverage quality of the whole monitoring area.If the moving target enters these monitoring blind spots,the whole network will lose its monitoring.Secondly,the node is powered by battery,and the energy it carries is very limited.Once the energy of the node is exhausted,there will be blind spots in the monitoring area,and the target tracking and information transmission will not be timely,resulting in network paralysis.Therefore,how to optimize the coverage efficiency and mobile energy consumption of nodes under the premise of ensuring better coverage effect is the research focus in this scheme.In another scheme,the traditional research on finding MEP only involves avoiding actual obstacles,but does not consider how to avoid areas with high coverage monitored by nodes,which is also of research value,and there is little research on coverage optimization based on finding MEP.Some scholars put forward a scheme to directly add sensors based on the found MEP,but this does not meet the economic requirements of low cost and the harsh deployment environment of WSNs,and it is difficult to add or replace nodes once deployed.Therefore,a theoretical breakthrough with stronger applicability is urgently needed.In this thesis,aiming at two different coverage optimization problems of anti-intrusion monitoring,adaptive virtual force-oriented bat algorithm,minimum exposure path determination algorithm based on ant colony algorithm and optimization strategy of barrier coverage are proposed respectively.The main research contents of this thesis are as follows.(1)Aiming at the first coverage optimization scheme of the whole area anti-intrusion monitoring,this thesis adopts the Bioinspired Bat Algorithm(BA)to optimize the coverage of WSNs.In order to ensure faster response ability and better coverage quality,the virtual force-oriented strategy is added to speed up the convergence of the algorithm,and the Levy flight strategy is introduced,so that BA can effectively jump out of the local optimal solution.Finally,the adaptive virtual force-guided bat algorithm(AVFBA)proposed in this thesis can provide a better and faster node deployment scheme,shorten the time cost,effectively improve the network coverage and coverage efficiency,reduce the average moving distance and reduce the network energy consumption.(2)Aiming at the second low-cost anti-intrusion monitoring coverage optimization scheme,in the MEP searching stage,the relationship between Ant Colony Optimization(ACO)and MEP problem is constructed,and the MEP searching is transformed into the shortest path problem innovatively.For different number of sensor nodes,a dynamic threshold strategy is proposed,and the threshold is set reasonably.The grid with coverage times greater than the threshold in the monitoring area is used as an obstacle,and the searched MEP successfully avoids the area with high coverage.The ant colony algorithm is improved by adding exposure factor to the state transition probability formula.Finally,the Improved Ant Colony Optimization-based Minimum Exposure Path Determination(IACOMEPD)proposed in this thesis can effectively avoid areas with high coverage and find MEPs more accurately.(3)Aiming at the second low-cost anti-intrusion monitoring coverage optimization scheme,the Optimization Strategy of Barrier Coverage(OSBC)is proposed in the coverage enhancement stage.By designing three redundant node judgment rules,the redundant nodes in the best barrier construction row are identified and transferred to the center of the nearest uncovered grid point to build the barrier.The exposure value of MEP in the monitoring area is increased,which effectively reduces the cost,improves the economy of the network,enhances the network monitoring ability and reduces the risk of illegal intrusion of the network.The final experimental results show that the AVFBA algorithm proposed in this thesis can effectively improve the network coverage and coverage efficiency,and reduce the average moving distance of nodes in the coverage optimization scheme of anti-intrusion monitoring in the whole region.In the low-cost anti-intrusion monitoring coverage optimization scheme,the IACO-MEPD algorithm proposed in this thesis looks for a smaller exposure value,while OSBC algorithm can improve the MEP exposure value and reduce the network deployment cost.